Apparatus and method of biometric determination using specialized optical spectroscopy systems

ABSTRACT

Methods and apparatuses for performing biometric determinations using optical spectroscopy of tissue. The biometric determinations that are disclosed include determination or verifications of identity, estimation of age, estimation of sex, determination of sample liveness and sample authenticity. The apparatuses disclosed are based upon discrete light sources such as light emitting diodes, laser diodes, vertical cavity surface emitting lasers, and broadband sources with multiple narrow-band optical filters. The multiple light sources are encoded in a manner that the tissue response for each source can be efficiently measured. The light sources are spaced at multiple distances from a detector to contribute differing information to the biometric determination task as do light sources with different wavelength characteristics. Apparatuses are disclosed that incorporate a spectral biometric sensor with a personal electronic device such as cellular telephones, personal digital assistants, wristwatches, electronic fobs for the purpose of providing secure biometric access to protected property.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a division of U.S. patent application Ser. No.09/874,740, filed Jun. 5, 2001, entitled “Apparatus and Method ofBiometric Determination Using Specialized Optical Spectroscopy Systems”(“the parent application”) which is incorporated herein by reference forall purposes. The parent application is related to U.S. patentapplication Ser. No. 09/832,534, filed Apr. 11, 2001, entitled“Apparatus and Method of Biometric Identification or Verification ofIndividuals using Optical Spectroscopy”, which is a continuation-in-partof U.S. patent application Ser. No. 09/415,594, filed Oct. 8, 1999,entitled “Apparatus and Method for Identification of Individuals byNear-Infrared Spectrum”; which is related to U.S. patent applicationSer. No. 09/174,812, filed Oct. 19, 1998, entitled “Method forNon-Invasive Analyte Measurement with Improved Optical Interface”; andU.S. patent application Ser. No. 08/871,366, filed Jun. 9, 1997,entitled “Diffuse Reflectance Monitoring Apparatus”, all assigned to thesame assignee as the present application, and the disclosures of whichare incorporated herein by reference.

TECHNICAL FIELD

This present invention relates generally to methods and systems forperforming biometric determinations of individuals utilizing opticalspectra of tissue. More specifically, the invention relates to methodsand systems for determining or verifying identity, determining orverifying age, determining or verifying sex, and determining orverifying liveness and authenticity of the sample being measured. Thepresent invention discloses methods and systems for gathering opticalinformation about the tissue using a combination of wavelengths andsource-detector separations. The present invention discloses a family ofcompact, special-purpose optical sensors operating in thenear-ultraviolet, visible, and near-infrared spectral regions that aresuitable for a variety of biometric determination tasks. The sensors canbe used in stand-alone, dedicated applications or can be incorporated ina variety of personal devices such as cellular telephones, personaldigital assistants, wrist watches, or electronic fobs to providepersonal biometric security to protect access to a variety of protectedproperty.

BACKGROUND OF THE INVENTION

Biometric determination is generally defined as the process of measuringand using one or more physical or behavioral features or attributes togain information about identity, age, or sex of a person, animal, orother biological entity. As well, in order to ensure security, thebiometric determination task may include further tasks that ensure thatthe sample being measured is authentic and being measured on a livingbeing. This latter test is referred to as a determination of liveness.

There are two common modes in which biometric determinations of identityoccur: one-to-many (identification) and one-to-one (verification).One-to-many identification attempts to answer the question of “do I knowyou?” The biometric measurement device collects a set of biometric dataand from this information alone it assesses whether the person is apreviously seen (“authorized”) individual. Systems that perform theone-to-many identification task, such as the FBI's Automatic FingerprintIdentification System (AFIS), are generally very expensive ($10 millionor more) and require many minutes to detect a match between an unknownsample and a large database containing hundreds of thousands or millionsof entries. The one-to-one mode of biometric analysis answers thequestion of, “are you who you say you are?” This mode is used in caseswhere an individual makes a claim of identity using a user name, apersonal identification number (PIN) or other code, a magnetic card, orother means, and the device collects a set of biometric data which ituses to confirm the identity of the person.

Although in general the one-to-many identification task is moredifficult than one-to-one, the two tasks become the same as the numberof recognized or authorized users for a given biometric device decreasesto just a single individual. Situations in which a biometricidentification task has only a small number of entries in theauthorization database are quite common. For example, biometric accessto a residence, to a personal automobile, to a personal computer, to acellular telephone, and to other such personal devices typically requirean authorization database of just a few people.

Biometric identification and verification is useful in manyapplications. Examples include verifying identity prior to activatingmachinery or gaining entry to a secure area. Another example would beidentification of an individual for matching that individual to recordson file for that individual, such as for matching hospital patientrecords especially when the individual's identity is unknown. Biometricidentification is also useful to match police records at the time asuspect is apprehended, but true identity of the suspect is not known.Additional uses of biometric identification or verification includeautomotive keyless start and entry applications, secure computer andnetwork access applications, automated financial transactionapplications, authorized handgun use applications, andtime-and-attendance applications. In general, protected property will bethe term used to describe all of the goods, places, services, andinformation that may require biometric authorization to access.

Current methods for biometric identification are manifold, but some ofthe most common techniques include fingerprint pattern matching, facialrecognition, hand geometry, iris scanning, and voice recognition. Eachof these technologies addresses the need for biometric identification tosome extent. However, due to cost, performance, or other issues, each ofthe existing methods has advantages and disadvantages relative to theother technologies.

There are currently many personal electronic devices that are used togain access to protected property but that do not include any biometriccapability. For example, electronic fobs are commonly used to gain entryto automobiles and to activate commercial and residential alarm systems.Wristwatches such as the Swatch Access models can be used to purchaseand download codes that allow easy entry to ski areas and other for-payrecreational sites. A wristwatch being sold by Xyloc permits access tocomputers, printers, networks, or other properly equipped hardware andsystems when the watch is in the vicinity of the protected system. Asmall electronic device known as an iButton sold by Dallas Semiconductorcan be put into a ring, key fob, wallet, watch, metal card or badge,that a person can carry and use to gain access to properly equippeddoors and other protected systems. However, an unauthorized user cangain access to any of the property protected by these systems by simplyobtaining a device from an authorized user. These devices do not havethe capability to distinguish between authorized and unauthorized usersand will work for anyone who possesses them. This deficiency representsa major security concern.

In U.S. Pat. No. 6,041,410, Hsu et al. disclose a personalidentification fob that employs fingerprint data. This system isspecified to contain memory to hold the fingerprint image, an imagecorrelater, a communication means employing a cyclic redundancy code,and a “door” that is controlled by the biometric system and allowsaccess to protected property. Hsu et al. generalize “door” as a means toaccess protected property including a building, a room, an automobile,and a financial account. The method disclosed relates to a door thatprotects property and its interaction with the fob, including a“wake-up” message and a series of steps to collect the biometric dataand compare it with reference data, determining a match, and thenactuating the device to provide access through the door.

One company that currently sells a personal identification unit isaffinitex, a division of AiT, and the product name is VeriMe. Because ofthe size of the fingerprint reader incorporated in the VeriMe product aswell as the batteries and control electronics, the unit is relativelylarge and is intended to be hung around the neck like a pendant. Incontrast, a long-standing desire of many in the biometric community is abiometric technology that can be discretely incorporated in a piece ofjewelry such as a wristwatch (for example, see Biometrics; AdvancedIdentity Verification, Julian Ashbourn, Springer, 2000, pp. 63-4).

There are a number of known biometric products and technologies thatrely on optical images of various tissue sites to perform a biometricdetermination. For example, in U.S. Pat. No. 4,537,484, Fowler, et al.describe an apparatus for collecting a fingerprint image using opticaltechniques. In U.S. Pat. No. 6,175,407, Sartor describes an apparatusfor collecting a palm image using optical techniques. In U.S. Pat. No.5,291,560, Daugman describes a method for collecting and processing anoptical image of the iris. In U.S. Pat. No. 5,793,881, Stiver et al.describe a system and method for collecting an image of the subcutaneousstructure of the hand using an imaging methodology. However, all ofthese technologies generate and use images of the tissue as the basisfor a biometric determination. The use of imaging generally requireshigh-quality expensive optical systems and an imaged region that is ofsufficient size to capture the necessary biometric detail. If the imagedregion is made too small, the biometric performance of these imagingsystems degrade. For this reason, contact imaging systems such asfingerprint and palm readers require a relatively large, smooth,accessible surface, limiting the range and form of products in whichsuch systems can be incorporated. Finally, because the determination ofa match between enrolled images and the test images is dependent on theorientation of the two images, such biometric systems have to correctfor these positional effects. For this reason, biometric systems thatrely on imaging techniques require a significant computational power anda sophisticated algorithm to correct for image displacements, rotationsand distortions, which leads to increased system cost and increased timerequired for user authentication.

As an alternative to imaging techniques, the use of spectral informationfor biometric determinations is disclosed in U.S. patent applicationSer. No. 09/832,534, filed Apr. 11, 2001, entitled “Apparatus and Methodof Biometric Identification or Verification of Individuals using OpticalSpectroscopy”, which is a continuation-in-part of U.S. patentapplication Ser. No. 09/415,594, filed Oct. 8, 1999, entitled “Apparatusand Method for Identification of Individuals by Near-Infrared Spectrum”.The equipment used to perform the measurements disclosed in theseapplications was based on relatively large and expensive multi-purposelaboratory-grade commercial spectrometers. The family of techniquesdisclosed in these applications is referred to as spectral biometrics.The disclosures of these applications are incorporated herein byreference.

It is well known that tissue spectra are generally affected by both theabsorption and scattering properties of the tissue. For many spectralmeasurement applications the portion of the measured spectra thatrepresent the absorption characteristics of the tissue are moreimportant for the measurement rather than the effects due to scatter.One technique for separating the two effects is known as radiallyresolved diffuse reflectance spectroscopy, which is based on collectingmultiple measurements with different source-detector separationdistances. This collection of data provides enough information toestimate and separate effects due to scatter and absorption (seeNichols, et al., Design and Testing of a White-Light, Steady-StateDiffuse Reflectance Spectrometer for Determination of Optical Propertiesof Highly Scattering Systems, Applied Optics, Jan. 1, 1997, 36(1), pp93-104.). Although the use of multiple source-detector separations is awell-known technique for analyte measurements in biological samples, theuse of similar measurement configurations for spectral biometricdeterminations has not been previously disclosed.

There is a need for an inexpensive, rugged and small spectrometer toperform spectral biometric determinations. One method that can be usedto construct such spectrometers is based on using multiple discretelight sources such as light emitting diodes (LEDs), laser diodes,vertical cavity surface emitting lasers (VCSELs), and narrow bandoptical filters coupled to a broad-band optical source such as anincandescent bulb or blackbody emitter, operating at differentwavelengths to illuminate and measure the optical properties of thesample at each of these wavelengths. These types of spectrometers areknown and used for collecting spectrometric information for manyapplications. For example, in U.S. Pat. No. 3,910,701, Henderson et al.disclose a spectrometer that incorporates a plurality of LED sources formeasuring a variety of biological samples. In U.S. Pat. No. 4,857,735,Noller discloses a spectrometer using one or more LEDs to measuresolution samples. In U.S. Pat. No. 5,257,086, Fately et al. disclose anoptical spectrometer having a multi-LED light source incorporatingHadamard or Fourier frequency encoding methods. However, there is a needfor a small, rugged, and inexpensive spectrometer with designs that arcoptimal for biometric determinations.

As part of the biometric determination task, there is a need forensuring that the sample being used for the biometric determination isalive. For example, U.S. Pat. No. 5,719,950 to Osten et al. disclose amethod and system to combine a biometric-specific measurement such asfingerprints, palm prints, voice prints, etc with a separate measurementof a non-specific biometric parameter such as skin temperature, pulse,electrocardiogram or tissue spectral features to ensure the liveness ofthe sample.

In addition to performing a biometric identification or verification andensuring that the sample being measured is living tissue, there may alsoexist a need to determine an estimate of the age, sex, and otherdemographic characteristics of the person under test as part of thebiometric determination task. For example, the U.S. Federal TradeCommission recently established a commission to examine the issue ofremotely determining age of a person who is attempting to access a website in order to block access by children to inappropriate sites. TheCommission on Online Child Protection (COPA) heard testimony on Jun. 9,2000 that indicated that then-known biometric techniques could not beused to aid the determination of a person's age based on any knownbiometric features.

BRIEF SUMMARY OF THE INVENTION

Detailed embodiments of the present invention are disclosed herein.However, it is to be understood that the disclosed embodiments aremerely exemplary of the present invention, which may be embodied invarious systems. Therefore, specific details disclosed herein are not tobe interpreted as limiting, but rather as a basis for the claims and asa representative basis for teaching one of skill in the art to variouslypractice the invention.

The present invention is based on Applicant's recognition that anaccurate, precise and repeatable tissue spectra of an individualincluding selected wavelengths in the near ultraviolet range, visiblerange, very near infrared range or near infrared range and combinationsof selected wavelengths from these ranges contains spectral features andcombinations of spectral features which are unique to that individual.The spectral range over which biometric determinations have beendemonstrated span wavelengths from 350 nm to 2500 nm, although it islikely that similar capabilities exist outside of this range.

The choice of which measurement wavelengths to use is driven in part bythe availability and cost of suitable illumination sources anddetectors. In the case of the discrete light sources disclosed in thisapplication, the most common and least expensive optical components workwith light in the wavelength region from 350-1000 nm. Such a system canbe constructed from silicon detector material and readily availableLEDs, laser diodes, VCSELs, or optical filters coupled to a bulb.However, other detectors and other light sources could also be used asalternative components or to span a greater spectral range or adifferent spectral range.

The present method and apparatus also provides for biometricdetermination of whether a sample being measured is living tissue, knownas a “liveness” determination. Further, the present system maintainshigh system security because the biometric device ensures that the exactsample it is operating on is real and alive, in addition to matching theproperties of the enrolled data. Thus, an accurate determination ofliveness precludes the use of simulated body parts and/or parts thathave been removed from authenticated individuals. It has been found thatthe spectroscopic signature of living tissue is substantially differentthan most other media (including dead tissue), and thus livenessdetermination is an integral part of the present biometric device andmethod.

The present method and apparatus can also be used to estimate or verifythe age of a person undergoing the biometric measurement. Further, thepresent method and apparatus can be used to estimate or verify the sexof the person undergoing the biometric measurement.

A variety of embodiments are disclosed herein for a sensor apparatusthat can obtain tissue spectra that can be utilized for biometricidentification determinations, liveness determinations, agedeterminations and sex determinations. These embodiments of the presentinvention are amenable to miniaturization and ruggedization forincorporation in a variety of systems. Such fixed-installationapplications include, but are not limited to, physical entry assuranceto workplaces, homes, hotels, secure industrial areas and othercontrolled sites; time and attendance monitoring; automotiveapplications such as keyless entry, keyless start, automotivepersonality setting, and mobile internet access; personal computer andnetwork security; secure health record access; automated financialtransactions; and authorized handgun use.

In addition to the fixed-system applications, the apparatus and methodsdisclosed in this application can be used in small personal biometricpackages such as smart cards, electronic fobs or wristwatches that theuser/owner/wearer can carry with them and provide biometrically-assuredauthorization to a variety of devices and systems. Such personalbiometric systems act as keys that provide access to protected propertyonly if activated by the authorized individual, and reduces oreliminates entry to the protected system by unauthorized people. Thus,the personal biometric devices of the present invention become a type ofsmart key that allow access to any system that interfaces to such deviceand for which the holder is authorized to access. Such systems and usescan include, but are not limited to, personal computers, network accessdevices, doors in office buildings and private residences,time-and-attendance systems, automobiles, security equipment, automatedfinancial transactions, cellular telephones, toll booths, electronicvending machine transactions and pay-per-entry events such as movies,etc.

Alternatively, as personal electronics such as personal digitalassistants (PDA) and cellular phones become integrated in a variety ofwireless applications, the present invention provides a means to confirmthe identity of the person using the device. This can be important whenwireless applications such as mobile commerce use such devices toauthorize monetary transfers or make purchases, while also allowingaccess to medical records and act as an electronic key for homes,offices and automobiles. By providing an integrated, compact, rugged,secure biometric system that can be used to confirm the identity of aperson attempting to use the PDA to access protected property, thepresent invention provides a capability that is applicable in manyeveryday life situations.

In addition to the application of the spectral biometric sensor as asingle biometric, the sensor and identification methods disclosed inthis application can also be used in conjunction with other biometrictechniques within a system to either increase the accuracy of the systemor increase the robustness of the system. In cases where greater systemsecurity is required, the spectral biometric technique may be combinedwith one or more other biometric methods and the results can be combinedto ensure a person's identity. Alternatively, the disclosed systems andmethods can be combined with other biometric techniques to offer morethan one method to identify a person in case one method is disabled dueto system failure or other reason, ensuring a more robust systemperformance overall.

One system for performing biometric determinations includes: an opticalsensor head consisting of one or more monochromatic illuminationsources, one or more detectors, and an optical sampler, all arrangedsuch that there exists a plurality of source-detector spacings or aplurality of different monochromatic wavelengths, or both; alight-source encoding system; a microprocessor with an input and outputdevice; a database including selected tissue spectral data forauthorized persons or a collection of spectral data for individualsagainst which unknown individual's would be checked; and a programrunning in the microprocessor for discriminating between a targetindividual's spectral data and the authorized spectral data orcollection of spectra database containing spectra for a group ofindividuals. The program can include software for performing an analysisfor liveness determination, age determination, and sex determinationbased on the measured spectral data.

These and various other advantages and features of novelty whichcharacterize the present invention are pointed out with particularity inthe claims annexed hereto and forming a part hereof However, for abetter understanding of the invention, its advantages, and the objectobtained by its use, reference should be made to the drawings which forma further part hereof, and to the accompanying descriptive matter inwhich there are illustrated and described preferred embodiments of thepresent invention.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, in which like reference numerals indicate correspondingparts or elements of preferred embodiments of the present inventionthroughout the several views:

FIG. 1 is a perspective view of a spectral biometric sensor head in onepreferred embodiment;

FIG. 2 is a schematic cross-sectional view of the biometric sensorelement coupled to the skin surface showing multiple mean optical paths;

FIG. 3 is a schematic top view of the biometric sensor incorporatingmultiple light sources arranged with variable source-detector distances;

FIG. 4 is a schematic representation of the top view of an alternativebiometric sensor incorporating multiple light sources arranged with acommon source-detector distance;

FIG. 5 is a schematic top view of an alternative biometric sensorincorporating multiple light sources and a waveguide/aperture plate toprovide variable source-detector distances;

FIG. 6 is a schematic top view of an alternative biometric sensorincluding multiple light sources and multiple detectors providingvariable source-detector separations;

FIG. 7 is a schematic top view of an alternative biometric sensorincorporating multiple light sources and a detector array for providingvariable source-detector separations;

FIG. 8 is a schematic representation of a personal biometric sensorbuilt into a key fob;

FIG. 9 is a schematic representation of a watch including a personalbiometric sensor built into a back faceplate of the watch;

FIG. 10 is a schematic of a laboratory spectrometer system that was usedto perform experiments to confirm performance of spectral biometricdevices;

FIG. 11 is a schematic diagram of an end view of a dual-path fiber opticsampler;

FIG. 12 is a graph depicting receiver-operator characteristics for thedual-path sampler of FIG. 11;

FIG. 13 is a graph depicting equal error rates for the dual-path sampleranalysis using variable numbers of discrete spectral elements;

FIG. 14 graphically depicts experimental results for age predictionutilizing an embodiment of the present invention;

FIG. 15 graphically depicts experimental results for a sex predictionutilizing an embodiment of the present invention;

FIG. 16 graphically depicts sex prediction ability versus the portion ofdata determined to be ambiguous;

FIG. 17 graphically depicts the results of liveness testing; and

FIG. 18 further details the liveness testing depicted in FIG. 17.

DETAILED DESCRIPTION OF THE INVENTION

Detailed embodiments of the present invention are disclosed herein.However, it is to be understood that the disclosed embodiments aremerely exemplary of the present invention which may be embodied invarious systems. Therefore, specific details disclosed herein are not tobe interpreted as limiting, but rather as a basis for the claims and asa representative basis for teaching one of skill in the art to variouslypractice the invention.

The present invention is based on Applicant's recognition that anaccurate, precise and repeatable tissue spectrum of an individual in thenear ultraviolet range, visible range, very near infrared, or nearinfrared spectral range and combinations of these ranges containsspectral features and combinations of spectral features which are uniqueto that individual. The present invention is further based on arecognition that proper analysis, utilizing discriminant analysistechniques, can identify these unique features or combinations, whichare not readily apparent in visual analysis of a spectral output, sothat an individual's identity may be determined by comparison of tissuespectral data taken at the time of use and compared to stored tissuespectral data from prior measurement.

In addition, the tissue spectrum has been found to not only containinformation that is unique to an individual, but also contains numerousfeatures and combinations of features that indicate whether suchspectral samples were taken while the sample was alive or not. Thephysiological effects that give rise to spectral features that indicatethe state of a sample (alive or dead) include but are not limited toblood perfusion, temperature, hydration status, glucose and otheranalyte levels, and overall state of tissue decay. Thus, the biometricidentification and verification methods of the present invention can bealso used in conjunction with, or separately from, the determination ofthe state of the liveness of the tissue. Tissue from other biologicalsystems (organs, animals, etc.) has also been found to have spectralcharacteristics that are distinctly different from human skin due todifferences in the tissue composition and form. Thus, the biometricidentification methods of the present invention can be also used inconjunction with or separately from the determination of whether thesample is human skin or some other tissue. In addition, it has beenfound that tissue-like substances such as collagen gelatin, latex, watersolutions, or others have spectral characteristics that are distinctlydifferent than human tissue due to differences in composition and form.The biometric identification and verification methods of the presentinvention can thus be used with or separately from the determinationwhether the sample is actual tissue or some other substance.

While utilizing the present invention, it has also been found that otherspectral features observed in the tissue spectrum relate to the age andsex of the person being measured. It is believed that these features aredue in part to the differences in dermal thickness between young and oldpeople and between males and females. Such changes in skin thickness andcomposition affect the optical characteristics of the tissue byaffecting the scattering properties of the sample. These properties inturn impose distinct spectral shapes on the measured tissue spectra,which can be extracted and used by appropriate multivariate techniquesto provide age and sex estimates.

Referring now to FIG. 1, a perspective view of an embodiment of atypical optical sensor head of the present invention is shown. Thesensor assembly 30 consists of a series or plurality of light sources 34arranged in a selected manner on a sensor head 32, which also containsone or more detectors 36. The sensor assembly 30 may also include powerconditioning electronics (not shown), which supply power to the lightsources 34 and may also include signal processing electronics (notshown) which amplify the resulting signal from the detector 36. Amulti-conductor cable 38 provides a means to power the sensor head andto transmit the detected signal back to the microprocessor or computer(not shown) that processes the spectral data.

The light sources 34 can be light emitting diodes (LEDs), laser diodes,vertical cavity surface emitting lasers (VCSELS), quartz tungstenhalogen incandescent bulbs with optical pass-band filters with opticalshutters, or a variety of other optical sources known in the art. Thelight sources 34 can each have the same wavelength characteristics orcan be comprised of sources with different center wavelengths in thespectral range from about 350 nm to about 2500 nm. In general, thecollection of light sources 34 can include some sources that have thesame wavelengths as others and some sources that are different. In apreferred embodiment, the light sources 34 includes sets of LEDs, laserdiodes, VCSELs, or other solid-state optoelectronic devices withdiffering wavelength characteristics that lie within the spectral rangefrom about 350 nm to about 1100 nm.

The detector 36 can be a single element or it can be a one- ortwo-dimensional array of elements. The detector type and material ischosen to be appropriate to the source wavelengths and the measurementsignal and timing requirements. These detectors can include PbS, PbSe,InSb, InGaAs, MCT, bolometers and micro-bolometer arrays. In a preferredembodiment where the light sources 34 are solid-state optoelectronicdevices operating in the spectral range from about 350 nm to about 1100nm, the preferred detector material is silicon.

The light sources 34 can be sequentially illuminated and extinguished tomeasure the tissue properties for each source by turning power to eachof them on and off. Alternatively, multiple light sources 34 can beelectronically modulated using encoding methods that are known to oneknowledgeable in the art. These encoding patterns include Fourierintensity modulation, Hadamard modulation, random modulation, and othermodulation methods.

FIG. 2 shows a cross-sectional view of the sensor head 32 of FIG. 1, foruse in diffuse reflectance measurements. Also shown is the tissue 40 incontact with the face 39 of the sensor head 32 and the mean opticalpaths 42, 44, 46, 48, 50, 52 of the light traveling from each lightsource 41, 43, 45, 47, 49, 51, respectively, to the detector 36. Inacquiring tissue spectral data, measurements can be made in at least twodifferent sampling modes. The optical geometry illustrated in FIG. 2 isknown as diffuse reflectance sampling geometry where the light sourcesand detector lie on the same side of the tissue. An alternative methodis known as transmission sampling, wherein light enters a thin tissueregion such as an earlobe or a fingertip on one side and then isdetected by a detector located on the other side of the tissue. Althoughlight in such regions as the silicon-region can penetrate tissue tosignificant depths of one centimeter or more, depending upon thewavelength, transmission sampling of the tissue limits the region of thebody that can be used. Thus, while either mode of sampling is applicableto the present invention, and especially to analysis utilizing light inthe silicon-region, a preferred and more versatile sampling method isbased upon reflected light.

Referring to FIG. 2, when the tissue is illuminated by a particularlight source 41, the resulting signal detected by detector 36 containsinformation about the tissue optical properties along a path between thesource 41 and detector 36. The actual path of any given photon is highlyerratic due to effects of optical scattering by the tissue, but the meanoptical path 42 is a more regular and smooth curve, as shown in thefigure.

This mean optical path is, in general, different for differentsource-detector separation distances. If another light source 51 islocated at the same distance from the detector 36 as light source 41 andthe two light sources have the same wavelength characteristics, theresulting signals can be combined to increase the resultingsignal-to-noise ratio of the measurement. If light source 51 has adifferent wavelength characteristic than light source 41 then, ingeneral, the resulting signals provide unique and useful informationabout the tissue optical properties, especially as they relate tospectral biometric determinations and should be analyzed as distinctdata points. In a similar manner, if two light sources have the samewavelength characteristics and are positioned at different distancesfrom the detector 36 (for example light sources 41 and 43) then theresulting information in the two signals is different and themeasurements should be recorded and analyzed as distinct data points.Differences in both wavelength characteristics and source-detectorseparation provide new and useful information about the opticalcharacteristics of the tissue 40.

In general, the detector 36 can be located in the center of the sensorhead or it can be offset to one side of the sensor head 32 in order toprovide for greater source-detector separation distances. The sensorhead 32 can be other shapes including oval, square and rectangular. Thesensor head 32 can also have a compound curvature on the optical surfaceto match the profile of the device in which it is mounted.

Light that reflects from the topmost layer of skin does not containsignificant information about the deeper tissue properties. In fact,reflections from the top surface of tissue (known as “specular” or“shunted” light) are detrimental to most optical measurements. For thisreason, FIG. 2 illustrates a sensor-head geometry wherein the detector36 is recessed from the sensor surface 39 in optically opaque material37 that makes up the body of the sensor head 32. The recessed placementof detector 36 minimizes the amount of light that can be detected afterreflecting off the first (epidermal) surface of the tissue. It can beseen that the same optical blocking effect could be produced byrecessing each of the light sources, or by recessing both the detectorand the light sources. Other equivalent means of optical blocking can bereadily established by one of ordinary skill in the art.

FIG. 3 shows a top view of the sensor head 32 with plurality lightsources 34 and a single detector 36 visible. This figure is intended tobe representative of configurations that allows for a variety of sources34 and detectors 36 that have variable spacing between them. In general,this configuration is most applicable in cases where a small number oflight sources 34 with different wavelength characteristics areavailable. In these cases, the variable distance between sources 34 anddetector 36 are used to gather additional optical information from thetissue.

Referring to FIG. 4, the light sources 34 can also be arranged to beequidistant from the detector 36. This configuration is most appropriatein cases where each light source 34 is a different wavelength andsufficient light sources can be obtained to achieve the desired accuracyresults for the system. An example of this occurs when the individuallight sources are the result of combining optical filters with one ormore broadband (e.g., incandescent) light sources. In this case, manyunique wavelength bands can be defined and each of the sources 34 can beplaced equidistant from the central detector 36.

An alternative embodiment of a variable source-detector configuration isillustrated in FIG. 5, which schematically depicts a top view of asensor 70 of this type. In this embodiment, the four different lightsources 71, 74, 77, 80 are arranged around a common detector 83. Fourdifferent light sources 71, 74, 77, 80 are shown for illustration butfewer or more can be used in a particular embodiment. Each of the lightsources 71, 74, 77, 80 is optically coupled to a different opticalwaveguide 72, 75, 78, 81. Each waveguide 72, 75, 78, 81 has individuallycontrollable electronic or mechanical optical shutters 73, 76, 79, 82.These optical shutters 73, 76, 79, 81 can be individually controlled toencode the light by allowing light to enter the tissue from a waveguide72, 75, 78, 81 at a predetermined position or positions. One method forimplementing optical shutters is using micro-electromechanical systems(MEMS) structures, which is a technology well known to one of ordinaryskill in the art. The light sources 71, 74, 77, 80 can be differentLEDs, laser diodes or VCSELs. Alternatively, one or more incandescentsources with different optical filters can be used to generate light ofdifferent wavelength characteristics to couple into each of thewaveguides 72, 75, 78, 81. As well, this MEMS aperture geometry could beused with other illumination sources and geometries illustrated in theother figures in this application.

Alternatively, multiple source-detector distances can also be achievedby using more than one detector element as shown in FIG. 6. FIG. 6schematically depicts a top view of a sensor 80 of this type. In thisembodiment, each of three different light sources 82, 84, 86 ispositioned relative to three detectors 81, 83, 85 such that the spacingbetween a given light source and each of the detectors is different. Forexample, the source detector spacing for a light source 82 is shortestwith respect to detector 85 and longest with respect to detector 83. Byturning on the light sources 82, 84, 86 in a sequential or encodedpattern and measuring the response at each of the three detectors 81,83, 85, the tissue characteristics for all of the availablesource-detector separations at all of the wavelengths can be measured.

The use of multiple detector elements and multiple illumination sourcescan be extended to using a detector array as shown in FIG. 7. FIG. 7schematically depicts a top view of a sensor 90 of this type. In thisembodiment, multiple light sources 92, 94, 96, 98 are placed at theperimeter of a detector array 99. The signal detected at each of thearray elements then represents a different source-detector separationwith respect to the light from a given light source. Many variants onthis configuration exist including the use of one-dimensional (1-D) ortwo-dimensional (2-D) arrays, and placing sources within the array aswell as on the periphery.

The detector(s) can be any material appropriate to the spectral regionbeing detected. For light in the region from about 350 nm to about 1100nm, a preferred detector material is silicon and can be implemented as asingle-element device, a collection of discrete elements, or a 1-D or2-D array, depending upon the system configuration and encoding methodused. For light in the region from about 1.25 to about 2.5 .mu.m, apreferred detector material is InGaAs and can also be implemented as asingle element, a collection of elements, or a 1-D or 2-D array.Additional detector materials and means of detection include InSb, Ge,MCT, PbS, PbSe, bolometers, and others known to one of ordinary skill inthe art.

Once the light passing though the tissue is detected, the signals can bedigitized and recorded by standard techniques. The recorded data canthen be processed directly or converted into absorbance spectra ornoised-scaled absorbance spectra as is known to one of ordinary skill inthe art. The data can then be used for spectral identification orverification by the methods described in U.S. patent application Ser.No. 09/832,534, filed Apr. 11, 2001, entitled “Apparatus and Method ofBiometric Identification or Verification of Individuals using OpticalSpectroscopy”, and U.S. patent application Ser. No. 09/415,594, filedOct. 8, 1999, entitled “Apparatus and Method for Identification ofIndividuals by Near-Infrared Spectrum”.

A small spectral biometric subassembly, such as those discussed above,can be embedded in a variety of systems and applications. The spectralbiometric reader can be configured as a dedicated system that isconnected to a PC or a network interface, an ATM, securing an entryway,or allowing access to a particular piece of electronics such as acellular phone. In this mode, one or more people can be enrolled in thebiometric system and use a particular reader to gain access to aparticular function or area.

Alternatively, the spectral biometric system can configured as apersonal biometric system that confirms the identity of the sole personauthorized to use the device, and transmits this authorization to anyproperly equipped PC, ATM, entryway, or piece of electronics thatrequires access authorization. One advantage of this latter approach isthat the personal biometric system can transmit an identifying code tothe requesting unit and then use the biometric signal to confirmauthorization, which implies that the system needs to perform averification task rather than the more difficult identification task.Yet, from the user's perspective, the system recognizes the user withoutan explicit need to identify himself or herself. Thus, the systemappears to operate in an identification mode, which is more convenientfor the user.

An additional advantage of a personal biometric system is that if anunauthorized person is able to defeat the personal biometric system codefor a particular biometric system-person combination, the personalbiometric system can be reset or replaced to use a new identifying codeand thus re-establish a secure biometric for the authorized person. Thiscapability is in contrast to multi-person biometric systems that basetheir authorization solely on a biometric signature (spectral, as wellas any of the other biometric techniques such as fingerprint, iris,facial, etc.). In this latter case, if an intruder is able to compromisethe system by somehow imitating the signal from an authorized user,there is no capability to change the biometric code since it is basedsolely on a fixed physiological characteristic of a person.

FIG. 8 shows one embodiment of a personal spectral biometric system 100in the configuration of an electronic key fob 102. The equidistantsensor configuration of FIG. 4 is shown for illustration purposes only.Any of the disclosed sensor configurations are application in theelectronic key fob. The illumination 104 and detection system 106 arebuilt into the fob 102, as is the means to collect and digitize thespectral information. In one embodiment, short-range wireless techniquesbased upon RF signals 103 can be transmitted to communicate between thefob and a corresponding reader (not shown) that allows access to the PC,entryway, etc. In another embodiment, an infrared optical signal can beused to transmit the information between the fob and the reader. Inanother embodiment, a direct electrical connection is establishedbetween the personal biometric system and the reader. The actualcomparison between the measured spectral data and the previouslyrecorded enrollment spectrum (template) can be made either within thefob or at the reader. In the former case, the logical operationsnecessary to perform the comparison are done within the fob and then asimple confirmed or denied signal is transmitted to the reader. In thelatter case, the most recent measured spectrum is transmitted to thereader and the comparison and decision is accomplished at the reader orat a host to which the reader is connected. In either case, thecommunication between the fob and the reader needs to be performed in asecure manner to avoid interception and unauthorized use of the system.Methods for ensuring secure communication between two devices are wellknown to one of ordinary skill in the art.

A second embodiment of a personal spectral biometric system 110 isdepicted in FIG. 9. In this case, the biometric reader 111 is built intothe case of a watch 112 and operates based upon signals detected fromthe skin in the area of the wrist. The operation of this system isidentical to the operation described for the biometric fob. FIG. 10shows the equidistant-sensor geometry of FIG. 4 for illustrationpurposes only. Any of the sensor geometries previously disclosed can beused in this application.

In addition to the watch or fob, similar biometric capability can bebuilt into other personal electronic devices. These devices includepersonal digital assistants (PDAs) and cellular telephones. In eachcase, the personal biometric system can provide user authorization toaccess both the device in which it is installed, as well as to provideauthorization for mobile commerce (M-Commerce) or other wirelesstransactions that the device is capable of performing.

The compact sensors disclosed can also be put into firearms to preventunauthorized usage. In particular, the biometric sensor could be placedin the handgrip of a weapon such as a handgun or other firearm to sensetissue properties while the gun is being held in a normal manner. Afurther capability of the apparatuses and methods disclosed in thisapplication is the ability to identify people who are to be explicitlyexcluded from accessing protected property as well as determining thosewho are authorized to access the property. This capability will improvethe biometric performance of the system with respect to thoseunauthorized people who are known to attempt to use the device, whichcould be particularly important in the case of a personal handgun. Inparticular, parents who own a biometrically enabled handgun can enrollthemselves as authorized users and also can enroll their children asexplicitly unauthorized users. In this way, parents could have furtherinsurance that children who are known to be in the same household as agun will not be able to use it.

It is also possible to use the explicit-denial capability of a biometricsystem in a fixed installation such as a home, place of business, or anautomobile. For example, a biometric system installed at the entryway ofa place of business can be used to admit authorized employees andtemporary workers. If an employee is fired or the term of the temporaryemployee expires, then their enrollment data can be shifted from theauthorized to the unauthorized database, and an explicit check is madeto deny access to the former employee if he or she attempts to enter.

Because of the nature of optical spectroscopy, it is difficult togenerate spectra of similar shape and absorbance characteristics withoutusing similar material for the sample. For this reason, many commonmaterials, such as latex and wax that are used to defeat other biometricsystems such as fingerprint readers or hand geometry systems areineffective tissue surrogates for a spectral biometric system. Byperforming a spectral comparison, most non-tissue samples will berejected, resulting in a strong countermeasure capability againstpotential intruders.

Similarly, many of the spectral features that are present in thewavelength ranges disclosed by this invention arc indicative of livingtissue. These features include oxy- and deoxy-hemoglobin bands,temperature effects, intracellular hydration, and others. These effectscontribute to the overall spectral signature of the sample beingmeasured and ensure that a matching sample is one that is part of aliving person and normally perfused. Thus, a good spectral comparisonensures the “liveness” of a sample and deters the use of dead or excisedtissue as a means to circumvent the spectral biometric system.

In some applications, such as Internet access authorization, it may beuseful to be able to verify the sex and/or age of the person using thespectral biometric system.

Because of both age- and sex-specific difference in skin structure andcomposition, the optical spectra change in systematic and indicativeways such that the age and sex can be estimated using the biometricspectral data.

In practicing the present invention, the tissue spectral data isdetermined by measuring the light intensity received by the outputsensor for the various light sources which give indications of theoptical properties of the tissue at different wavelengths and/or atdifferent source-detector separations. As is well known to one ofordinary skill in the art, the signal produced by the detector inresponse to the incident light levels can be converted into spectraldata that can be recorded and used for subsequent analysis forenrollment or authorization of identity.

Experimental Results

A laboratory experiment was performed to test and confirm the premisethat discrete wavelength light sources could be used for biometricdetermination tasks and that further advantage could be gained byarranging the same sources with different source-detector spacings. FIG.10 shows a schematic of the laboratory system that was used in thisexperiment. This system used an illumination subsystem 100 thatincorporated a 100 W quartz tungsten halogen bulb 102 and some opticalfilters 104 to transmit light in the 1.25 to 2.5 .mu.m spectral range.The light was directed into a fiber-optic optical sampler 106, which wasused to take diffuse reflectance optical measurements of the volarsurface of the forearm. Diffusely reflected light collected by thesampler 106 was then directed into a Fourier transform infrared (FTIR)spectrometer 108 and detected by an extended range indium galliumarsenide (InGaAs) detector 110. The spectrometer was a Perkin Elmer 2000FTIR operating with a spectral resolution of 16 cm.sup.-1. The resultinginterferogram data were digitized, stored and converted to spectral datausing techniques well known to one of ordinary skill in the art.

The optical sampler 106 included a sample head 120 which was capable ofcollecting tissue spectral data using two different source-detectorspacings. FIG. 11 shows a top view of the optical sampler or sample head120 including three different optical fiber groupings: an outer ring121, an inner ring 122 and a central bundle 123. The outer ring ofoptical fibers 121 and inner ring of optical fibers 122 were used toilluminate the tissue and the central bundle of fibers 123 was used tocollect the diffusely reflected light. An optical switch (not shown) wasbuilt into the optical sampler subsystem such that either the outer ringof optical fibers 121 or the inner ring of optical fibers 122 wasilluminating the tissue at any one time. The center-to-center spacing ofthe inner ring fibers 122 to the center detection bundle 123 wasapproximately 0.5 mm while the outer ring 121 separation wasapproximately 0.7 mm. Thus, spectra collected when the outer ring wasilluminating the tissue had a longer and deeper average path length thanspectra collected with inner ring 122 illumination. The optical systemwas set up so spectra were collected alternately using inner and outerillumination closely spaced in time.

Twenty-two diabetic subjects participated in a study, which spanned atotal duration of 16 weeks. Each person in the study was measured duringtwo separate visits per week for each of the first 7 weeks of the study.There was then an 8-week gap, followed by one additional week of studywhere each person again was measured during two separate visits. Duringeach measurement visit, multiple (5) optical samples were collected fromthe underside of their left forearm. Each optical sample consisted of 90seconds of measurement time.

The optical samples collected by the sampler shown in FIG. 11 were usedto simulate a discrete source configuration similar to that shown inFIG. 3. Although the system shown in FIG. 11 is a broadband illuminationsystem, the spectral data collected on this laboratory system werepost-processed to emulate a discrete wavelength system. A small numberof uniformly spaced, discrete spectral elements (variously 4, 6, 10, or20) were selected from the continuous spectral data and used forsubsequent biometric analysis using the same type of analysis describedpreviously. The biometric determinations were made in a manner verysimilar to the technique described in U.S. patent application Ser. No.09/832,534, filed Apr. 11, 2001, entitled “Apparatus and Method ofBiometric Identification or Verification of Individuals using OpticalSpectroscopy”. In particular, the biometric analysis was performed byrandomly selecting a small number of subjects' data as from authorizedusers (“validation”), a different small subset as non-authorized users(“intruders”), and the remaining subjects' data were used to build acalibration set. Due to the relatively small number of subjects, theanalysis used six random subjects for validation and two as intruders.This analysis was repeated 10 times and output was pooled to achievestable results.

The calibration data were processed to produce generic data as describedin U.S. Pat. No. 6,157,041, entitled “Methods and Apparatus forTailoring Spectroscopic

Calibration Models”. A PCA decomposition of these data was performed togenerate 50 eigenvectors and scores. The scores were then analyzed todetermine the 20 factors that had the largest values for the ratio ofthe between-person variation to the within-person variation for each setof scores.

The first two samples for each of the validation subject's data wereaveraged and used as the initial enrollment spectra. Each of theremaining validation spectra were taken in temporal sequence andsubtracted from the enrollment spectrum. This spectral difference wasthen presented to the selected calibration factors and a Mahalanobisdistance was calculated. If the Mahalanobis distance was below a certainthreshold value, the validation spectrum was deemed valid, and aweighted sum of the validation spectrum (0.2) and the enrollmentspectrum (0.8) was used to update the enrollment spectrum. This processwas repeated for multiple threshold values. One of ordinary skill in theart will recognize that the Spectral F-Ratio could be used instead of orin conjunction with the Mahalanobis distance metric to perform theidentity determinations. The intruder data was processed in a similarmanner as the validation data using the same threshold values.

This analysis was applied to spectral data from inner ring illumination,from outer-ring illumination, and to a data set that concatenated theselected data from both inner-and outer-ring illumination. This lattercase simulated the condition where one pair of some number, N, ofdifferent discrete sources were used for illumination at two differentsource-detector distances and data were collected for each of the 2Nsources separately.

The results of this analysis are shown in FIGS. 12 and 13. FIG. 12depicts the receiver-operator characteristic (ROC) curves for the casewhere 20 of the spectral elements were used for biometric identificationtasks. The equal error rate (EER, defined as the false acceptancerate=false rejection rate) of the inner-ring data is 2.0% while theouter-ring data yields an EER of 1.6%. In contrast, a spectral data setmade up of both of the inner- and outer-ring spectral elements gives animproved EER of 0.7%. FIG. 13 shows the EER for all three samplingconditions for cases where 4, 6, 10, and 20 elements are used foranalysis. In all cases, the combined-ring data performs much better thaneither of the separate channels, indicating that additional biometricinformation is available by using the same wavelengths to measure tissuewith multiple source-detector separations.

The ability to assess age using spectral data was tested using the NIRspectra from a multi-person study that was conducted using alaboratory-grade FTIR system similar to that shown in FIGS. 10 and 11.However, the light source 102 was a 40 W quartz tungsten halogen bulb,the FTIR spectrometer 108 was a Bomcm WorkIR, and the optical sampler106 consisted of a just a single illumination ring and a centraldetector fiber bundle similar to the inner ring 122 and central bundle123 shown in FIG. 11.

The data were collected from 87 diabetic people who participated in aportion of a 17-week study. Approximately half of the peopleparticipated in the study for 6 weeks and half participated for 11weeks. In either case, each person was measured during two separatevisits per week for each week they participated in the study. Duringeach measurement visit, multiple (3-5) optical samples were collectedfrom the underside of their left forearm. Each optical sample consistedof 90 seconds of measurement time. A total of more than 5100 opticalsamples were collected on this study group. The resulting intensityspectra were log-transformed to pseudo-absorbance data and a scalefunction was applied to the spectra to make the spectral noisecharacteristics uniform. Standard outlier metrics (Mahalanobis Distanceand Spectral F-Ratio) were applied to the resulting scaled absorbancedata to remove outlying spectra before subsequent processing.

The scaled absorbance spectra and the corresponding ages of the subjectwere used in conjunction with the partial least squares (PLS)multivariate calibration algorithm to determine the age-predictionaccuracy. A person-out cross validation was performed, giving theresults shown in FIG. 14 where “SEP” is standard error of prediction,which is a one-standard-deviation measure of the error. It can be seenthat age predictions with an SEP better than 6 years is possible basedupon NIR tissue spectra.

A similar multivariate analysis was performed to determine sexprediction capability. In this case, each of the NIR spectra from the 87subjects was assigned a reference value of either 0 or 1 based upon thesex of the person from whom the spectrum was measured. These spectraldata and reference values were then processed using PLS and asubject-out cross-validation to determine sex predictions. Predictedvalues greater than 0.5 were assigned a value of 1 and predictions lessthan 0.5 were assigned a 0. The results of this analysis are given inFIG. 15, where it can be seen that approximately 85% of the spectrayielded accurate sex predictions. In some of these cases, the rawpredictions were close to the threshold value of 0.5, which implies theywere suspect and ambiguous. If those predictions closest to thethreshold are eliminated as ambiguous, the prediction ability on theremaining samples is improved. FIG. 16 shows how the prediction abilityimproves as a function of how often a spectrum is considered ambiguous.

The ability of a spectral biometric to discriminate between live tissueand other sample types is shown in FIGS. 17 and 18. The experiment thatgave these results was based on a demonstration that was set up toperform an identification task among a small group of enrolled people.In this experiment, several persons enrolled as valid users on a systemsimilar to the one described in the NIR 87 person analysis section,above. One of the valid users then presented themselves to the systemalong with another person who was not enrolled in the system. As well, alatex glove was filled with a saline solution and used to collectanother test sample. Finally, a piece of cowhide was also measured onthe system as a test sample. The results of this experiment are shown inFIG. 17, where it can be seen that the latex glove produces severelyinflated matching metrics. FIG. 18 shows a blowup of FIG. 18, where itcan also be seen that even a closely matched tissue sample such as thecowhide produces greatly inflated results. The sample taken from theperson who is authorized matches best, while the unauthorized person'ssample shows a marked inflation relative to the other valid user'ssample.

New characteristics and advantages of the invention covered by thisdocument have been set forth in the foregoing description. It will beunderstood, however, that this disclosure is, in many respects, onlyillustrative. Changes may be made in details, particularly in matters ofshape, size, and arrangement of parts, without exceeding the scope ofthe invention. The scope of the invention is, of course, defined in thelanguage in which the appended claims are expressed.

1.-11. (canceled)
 12. A method of determining a liveness state of asample, the method comprising: illuminating the sample with lightemitted from a light source; detecting light emanating from the samplewith a plurality of light detectors having different separations fromthe light source; and analyzing the detected light to determine whetherthe sample comprises living tissue.
 13. The method recited in claim 12wherein the light emitted from the light source comprises near-infraredlight.
 14. The method recited in claim 12 wherein the light source andthe plurality of light detectors are on opposite sides of the sample.15. The method recited in claim 12 wherein the light source and theplurality of light detectors are on the same side of the sample.
 16. Themethod recited in claim 12 wherein analyzing the detected lightcomprises analyzing the detected light to determine whether the samplecomprises living human tissue.
 17. The method recited in claim 12wherein the light source comprises a plurality of light sources, theplurality of light sources and plurality of light detectors defining aplurality of different light-source-light-detector separations.
 18. Themethod recited in claim 17 wherein the plurality of light sourcescomprise light sources having different center wavelengths.
 19. Themethod recited in claim 17 wherein the plurality of light sources havethe same wavelength characteristics.
 20. The method recited in claim 12wherein analyzing the detected light comprises: converting the detectedlight to an electrical signal; and digitizing the electrical signal. 21.The method recited in claim 20 wherein analyzing the detected lightfurther comprises performing a spectral comparison with the digitizedelectrical signal.
 22. The method recited in claim 12 wherein analyzingthe detected light further comprises performing a biometricidentification or biometric identity verification with the sample.
 23. Amethod of determining a liveness state of a sample, the methodcomprising: illuminating the sample with near-infrared light emittedfrom a light source; detecting light emanating from the sample with aplurality of light detectors disposed on a same side of the sample andhaving different separations from the light source; spectrally analyzingthe detected light to determine whether the sample comprises livinghuman tissue.
 24. A sensor comprising: a light source; a plurality oflight detectors having different separations from the light source; amicroprocessor or computer adapted to determine whether a samplecomprises living tissue with light received by the light detector whenthe sapmle is illuminated with light emitted from the light source. 25.The sensor recited in claim 24 wherein the light source comprises anear-infrared light source.
 26. The sensor recited in claim 24 whereinthe light source and the plurality of light detectors are on oppositesides of the sample.
 27. The sensor recited in claim 24 wherein thelight source and the plurality of light detectors are on the same sideof the sample.
 28. The sensor recited in claim 24 wherein themicroprocessor or computer is adapted to determine whether the samplecomprises living human tissue.
 29. The sensor recited in claim 24wherein the light source comprises a plurality of light sources, theplurality of light sources and plurality of light detectors defining aplurality of different light-source-light-detector separations.
 30. Thesensor recited in claim 29 wherein the plurality of light sourcescomprise light sources having different center wavelengths.
 31. Thesensor recited in claim 29 wherein the plurality of light sources havethe same wavelength characteristics.
 32. The sensor recited in claim 24wherein the microprocessor or computer is adapted to determine whetherthe sample comprises living tissue by converting the detected light toan electrical signal, digitizing the electrical signal, and performing aspectral comparison with the digitized electrical signal.
 33. The sensorrecited in claim 24 wherein the microprocessor or computer is furtheradapted to analyze the received light to perform a biometricidentification or a biometric identity verification with the sample. 34.A sensor comprising: a near-infrared light source; a plurality of lightdetectors disposed on the same side of a sample as the infrared lightsource; and a microprocessor or computer adapted to determine whetherthe sample comprises living human tissue by spectrally analyzing lightreceived by the plurality of light detectors when the sample isilluminated with light emitted from the infrared light source.